scholarly journals Experimental study of railway bridge scouring and proposal of remedial measures-A case study of bridge number 30, Harrow River.

2020 ◽  
Vol 899 ◽  
pp. 012015
Author(s):  
Muhammad Sohail Javed ◽  
Naeem Ejaz
Keyword(s):  
Experimental Study ◽  
Remedial Measures ◽  
Railway Bridge ◽  
Bridge Number

scholarly journals An Experimental Study on the Sources of Strontium in Mineral Water and General Rules of Its Dissolution—A Case Study of Chengde, Hebei

Water ◽  
2021 ◽  
Vol 13 (5) ◽  
pp. 699
Author(s):  
Ruifeng Wang ◽  
Xiong Wu ◽  
Yanliang Zhai ◽  
Yuxuan Su ◽  
Chenhui Liu
Keyword(s):  
Experimental Study ◽  
Mineral Water ◽  
Surrounding Rock ◽  
Mechanism Of Formation ◽  
High Quality ◽  
General Rules ◽  
Leaching Experiment ◽  
High Level ◽  
Impact Experiments

Chengde City boasts a wealth of high-quality mineral water resources characterized by a high level of strontium (Sr), a low level of sodium, and low alkalinity. In order to study the mechanism of formation of Sr-bearing mineral water in Chengde and to scientifically guide future mineral water exploration, taking three typical mineral water exploration areas in Chengde as examples, this paper studies the sources of Sr in mineral water and the general rules of its dissolution via a laboratory static leaching experiment and impact experiments, and it provides an analysis of the characteristics of typical rock samples. The research results indicate that the content of Sr in surrounding rock and the characteristics of minerals existing in surrounding rock jointly control the dissolution of Sr in water; that CO2 can promote the formation of mineral water containing Sr; and that temperature increases may boost the dissolution of Sr from carbonate minerals but also inhibit the dissolution of Sr from silicate minerals.

Case Study of the 156 m Simply Supported Steel Truss Railway Bridge

2017 ◽  
Vol 27 (4) ◽  
pp. 563-568 ◽  
Author(s):  
Xiangdong Yu ◽  
Yongle Deng ◽  
Bin Yan
Keyword(s):  
Railway Bridge ◽  
Simply Supported ◽  
Steel Truss

Underlying Determinants of Housing Location: a Case Study from Swaziland

1973 ◽  
Vol 11 (2) ◽  
pp. 211-225 ◽  
Author(s):  
John P. Lea
Keyword(s):  
Urban Growth ◽  
Industrial Location ◽  
Remedial Measures ◽  
National Plan ◽  
Short Term ◽  
Housing Needs ◽  
Short Term Effects

It is a comparatively recent development that places housing not only as one of the main targets in the national plan, but also as a vital means of achieving other social and economic objectives.1 Admirable though this may be, a number of difficulties can arise in practice, particularly with regard to the question of new housing where many dwellings may be on unsuitable sites and require relocation or extensive redevelopment. The point is that remedial measures are likely to have only short-term effects, unless several underlying – and often conflicting – variables are taken into account. Four such variables have assumed importance in the planning for future housing needs in the Greater Manzini Area of Swaziland, and it is the purpose of this article to illustrate how policies relating to industrial location, urban growth, and housing, interact with the tenurial system in force.

Twitter Users' Classification Based on Interest

2020 ◽  
Vol 10 (1) ◽  
pp. 1-12
Author(s):  
Noura A. AlSomaikhi ◽  
Zakarya A. Alzamil
Keyword(s):  
Machine Learning ◽  
Experimental Study ◽  
Knowledge Sharing ◽  
Naive Bayes ◽  
Learning Algorithm ◽  
Machine Learning Algorithm ◽  
Software System ◽  
Web Based ◽  
Twitter Users

Microblogging platforms, such as Twitter, have become a popular interaction media that are used widely for different daily purposes, such as communication and knowledge sharing. Understanding the behaviors and interests of these platforms' users become a challenge that can help in different areas such as recommendation and filtering. In this article, an approach is proposed for classifying Twitter users with respect to their interests based on their Arabic tweets. A Multinomial Naïve Bayes machine learning algorithm is used for such classification. The proposed approach has been developed as a web-based software system that is integrated with Twitter using Twitter API. An experimental study on Arabic tweets has been investigated on the proposed system as a case study.

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